Ontogeny Research Articles

Taxonomic resolution of the hillstream suck-loach Beaufortia pingi species group (Cypriniformes, Gastromyzontidae) and two new species from Southwest China– Beaufortia granulopinna and Beaufortia viridis

Two new species, Beaufortia granulopinna and Beaufortia viridis, are described from the upper Pearl River system in southwest China. Both species share the characteristics of the Beaufortia pingi species group, including prominent vertical stripes on the lateral body and pinnate-type lower lips, distinguishing them from other Beaufortia species. Beaufortia granulopinna is differentiated from other species in the group by possessing a unique set of characteristics: the presence of well-developed prominent tubercles on the first 6–9 pectoral fin rays in adults; and a significant proportion (54.76%) of individuals experiencing blurriness or absence of vertical stripes in the mid-section of the lateral body upon reaching adulthood. The minimum interspecific genetic distance within the genus based on mitochondrial cytb gene sequences is 10.80%. Beaufortia viridis is distinguished from other species in the group by consistently exhibiting vertical stripes of uniform length, width, and spacing across all stages of growth; the absence of tubercles on the branched rays of pectoral fins; and a body coloration of dark cyan to green. The minimum interspecific genetic distance within the genus based on mitochondrial cytb gene sequences is 4.60%. Molecular phylogenetic results confirm that the Beaufortia pingi species group forms a monophyletic clade, which is congruent with morphological classification findings. This study also addresses and resolves the taxonomic ambiguity surrounding Beaufortia pingi and Beaufortia zebroida, providing a redescription of these taxa.

Taxonomic resolution of the hillstream suck-loach Beaufortia pingi species group (Cypriniformes, Gastromyzontidae) and two new species from Southwest China– Beaufortia granulopinna and Beaufortia viridis

Two new species, Beaufortia granulopinna and Beaufortia viridis, are described from the upper Pearl River system in southwest China. Both species share the characteristics of the Beaufortia pingi species group, including prominent vertical stripes on the lateral body and pinnate-type lower lips, distinguishing them from other Beaufortia species. Beaufortia granulopinna is differentiated from other species in the group by possessing a unique set of characteristics: the presence of well-developed prominent tubercles on the first 6–9 pectoral fin rays in adults; and a significant proportion (54.76%) of individuals experiencing blurriness or absence of vertical stripes in the mid-section of the lateral body upon reaching adulthood. The minimum interspecific genetic distance within the genus based on mitochondrial cytb gene sequences is 10.80%. Beaufortia viridis is distinguished from other species in the group by consistently exhibiting vertical stripes of uniform length, width, and spacing across all stages of growth; the absence of tubercles on the branched rays of pectoral fins; and a body coloration of dark cyan to green. The minimum interspecific genetic distance within the genus based on mitochondrial cytb gene sequences is 4.60%. Molecular phylogenetic results confirm that the Beaufortia pingi species group forms a monophyletic clade, which is congruent with morphological classification findings. This study also addresses and resolves the taxonomic ambiguity surrounding Beaufortia pingi and Beaufortia zebroida, providing a redescription of these taxa.

Vegetation structure of associated flora in Amorphophallus gigas Teijsm. & Binn. (Araceae) habitats, North Padang Lawas Regency, North Sumatra

Amorphophallus gigas, a native aroid species found in the tropical forests of Sumatra, Indonesia, lacks robust population data despite previous spatial distribution studies. While not officially protected, A. gigas is considered rare in field documentation and faces potential habitat loss due to its proximity to the popular corpse flower. This 2023 study conducted in Halongonan District, North Padang Lawas Regency, North Sumatra, Indonesia, aimed to gather information on the habitat characteristics and associated flora of A. gigas to guide land conservation initiatives. The research focused on a forested area within three villages: Bargot Topong Julu, Napa Lancat, and Pangirkiran, utilizing a purposive random sampling approach. Plots covering 1 ha each were selected based on Amorphophallus in the generative phase across various land covers. Ecological analysis and indices were derived from collected vegetation data. The survey unveiled varying numbers of generative and vegetative A. gigas individuals across the three study sites. The understorey community at each site exhibited different levels of association with A. gigas, with Selaginella willdenowii, Clidemia hirta, and Leersia virginica showing strong positive correlations. The floral community in A. gigas habitats displayed diverse species richness and diversity across different growth stages and locations. Findings suggest that altitude, slope, pH, light intensity, air temperature, and humidity may influence A. gigas abundance in distinct ways. This study offers valuable insights into the biological and ecological factors influencing the distribution and abundance of A. gigas populations, providing guidance for conservation and management efforts.

Vegetation structure of associated flora in Amorphophallus gigas Teijsm. & Binn. (Araceae) habitats, North Padang Lawas Regency, North Sumatra

Amorphophallus gigas, a native aroid species found in the tropical forests of Sumatra, Indonesia, lacks robust population data despite previous spatial distribution studies. While not officially protected, A. gigas is considered rare in field documentation and faces potential habitat loss due to its proximity to the popular corpse flower. This 2023 study conducted in Halongonan District, North Padang Lawas Regency, North Sumatra, Indonesia, aimed to gather information on the habitat characteristics and associated flora of A. gigas to guide land conservation initiatives. The research focused on a forested area within three villages: Bargot Topong Julu, Napa Lancat, and Pangirkiran, utilizing a purposive random sampling approach. Plots covering 1 ha each were selected based on Amorphophallus in the generative phase across various land covers. Ecological analysis and indices were derived from collected vegetation data. The survey unveiled varying numbers of generative and vegetative A. gigas individuals across the three study sites. The understorey community at each site exhibited different levels of association with A. gigas, with Selaginella willdenowii, Clidemia hirta, and Leersia virginica showing strong positive correlations. The floral community in A. gigas habitats displayed diverse species richness and diversity across different growth stages and locations. Findings suggest that altitude, slope, pH, light intensity, air temperature, and humidity may influence A. gigas abundance in distinct ways. This study offers valuable insights into the biological and ecological factors influencing the distribution and abundance of A. gigas populations, providing guidance for conservation and management efforts.

Genome-wide identification and expression analysis of the CONSTANS-like family in potato (Solanum tuberosum L.).

The CONSTANS-like (COL) gene plays important roles in plant growth, development, and abiotic stress. A total of 15 COL genes are unevenly distributed on eight chromosomes in the potato genome. The amino acid length of the family members was 347-453 aa, the molecular weight was 38.65-49.92 kD, and the isoelectric point was 5.13-6.09. The StCOL family can be divided into three subfamilies by evolutionary tree analysis, with conserved motifs and similar gene structure positions in each subfamily. The analysis of promoter cis-acting elements showed 17 cis-acting elements related to plant hormones, stress, and light response. Collinearity analysis of COL genes of tomato, potato, and Arabidopsis showed that 13 StCOL genes in the different species may have a common ancestor. A total of 10 conserved motifs and six kinds of post-translational modifications in the 15 StCOL proteins were identified. The 15 StCOL genes exhibit a genomic structure consisting of exons and introns, typically ranging from two to four in number. The results showed that 10 genes displayed significant expression across all potato tissues, while the remaining five genes were down-expressed in potato transcriptome data. The quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis exhibited differential expression of 8 StCOL genes in the potato leaves and tubers at different growth stages, as well as 7 StCOL genes under 2°C treatment conditions. These results suggested that the StCOL gene family may play an important role in regulating potato tuberization and responding to cold stress.

Determinants of thinness among school adolescents in Legehida district, Amhara region, north east Ethiopia: an unmatched case-control study

BackgroundAdolescence is a critical stage of human growth and development, and adolescent nutritional status is a significant predictor of health outcomes. However, adolescents in developing countries, including Ethiopia, have received little attention from nutrition-related programs in recent decades. Consequently, malnutrition among adolescents is a widespread issue in these regions.ObjectiveThe study aimed to identify the determinants of thinness among school adolescents in the Legehida district of South Wollo Zone, Northeastern Ethiopia.MethodsA school-based, unmatched case-control study was conducted from January 20 to February 2, 2019. A total of 525 school-aged adolescents (175 cases and 350 controls) from the Legehida district were enrolled using a multistage sampling technique. Data were collected through interview-administered questionnaires and anthropometric measurements. EpiData version 3.1 was used for data entry, while Anthroplus software was employed for anthropometric measurement entry and analysis. The data were then exported to SPSS version 25 for further analysis. Bivariate and multivariable logistic regression analyses were performed to assess the determinants of adolescent thinness.ResultsIn this study, thinness among school adolescents was significantly associated with several factors: the absence of a latrine at home [AOR = 8.2, 95% CI (3.8, 8.17)], meal skipping per day [AOR = 3.1, 95% CI (1.2, 7.3)], inadequate consumption of fruits and vegetables [AOR = 7.5, 95% CI (3.9, 14.5)], having more than four household members [AOR = 13.6, 95% CI (7.1, 26)], and the consumption of unsafe water [AOR = 7.7, 95% CI (3.8, 15.6)].Conclusions and recommendationsThe absence of latrines and access to clean water, dietary factors, and family size emerged as significant contributors to adolescent thinness in this study. Addressing the nutritional challenges faced by adolescents will require collaborative efforts across sectors.

Screening the Potential f Fungal Derived Bioherbicide in Weed Management

Synthetic herbicides have long been a cornerstone of modern agriculture, providing effective weed control but often at significant environmental and health costs. These chemicals can persist in the environment, leach into groundwater, and harm non-target organisms, including humans. Additionally, the overuse of synthetic herbicides has led to the development of herbicide-resistant weeds, further complicating weed management strategies. In response to these challenges, researchers and farmers alike are increasingly turning to bioherbicides derived from fungi as a sustainable alternative. Fungal bioherbicides harness the natural antagonistic properties of fungi to target weeds. Unlike synthetic herbicides, which are chemically synthesized and often broad-spectrum in action, fungal bioherbicides utilize either the fungi themselves as pathogens or their metabolites to disrupt weed growth. This approach offers several distinct advantages:Target Specificity: Fungal bioherbicides can be highly specific to certain weed species or even to specific stages of weed growth. This specificity reduces collateral damage to non-target plants and organisms, making them particularly suitable for environmentally sensitive areas such as organic farms, riparian zones, and protected ecosystems. Environmental Friendliness: Unlike synthetic herbicides that can persist in the environment and accumulate in soil and water bodies, fungal bioherbicides generally have lower persistence. They degrade more rapidly and often have minimal impact on non-target organisms, thereby preserving biodiversity and ecosystem health. Reduced Risk of Resistance: Synthetic herbicides often face the challenge of herbicide-resistant weeds, which evolve due to continuous and widespread use. Fungal bioherbicides, by contrast, pose a lower risk of resistance development. This is because they typically act through multiple modes of action or biochemical pathways within the weed, making it harder for weeds to develop resistance mechanisms. Research into fungal-derived bioherbicides is actively exploring and harnessing these advantages. Scientists are screening diverse fungal species to identify potent pathogens or metabolites that effectively inhibit weed growth. Moreover, advances in biotechnology and genetic engineering allow for the enhancement of fungal strains to optimize their bioherbicidal properties while ensuring safety and efficacy. One promising example is the use of fungal pathogens like Phomamacrostoma and Colletotrichum truncatum, which have demonstrated efficacy against various weed species including common agricultural weeds like velvetleaf and pigweed. These fungi infect weeds through mechanisms such as spore attachment, penetration of plant tissues, and secretion of phytotoxic metabolites that inhibit weed growth. In addition to their direct impact on weed management, fungal bioherbicides contribute to sustainable agricultural practices by reducing reliance on synthetic chemicals. They align with principles of integrated pest management (IPM) by offering a biological control method that complements cultural and mechanical weed control strategies. Moving forward, continued research and development efforts are essential to refine fungal bioherbicides, optimize application techniques, and expand their practical use in diverse agricultural settings. Challenges such as formulation stability, cost-effectiveness, and regulatory approvals also need to be addressed to facilitate widespread adoption by farmers.

Determinants of thinness among school adolescents in Legehida district, Amhara region, north east Ethiopia: an unmatched case-control study

BackgroundAdolescence is a critical stage of human growth and development, and adolescent nutritional status is a significant predictor of health outcomes. However, adolescents in developing countries, including Ethiopia, have received little attention from nutrition-related programs in recent decades. Consequently, malnutrition among adolescents is a widespread issue in these regions.ObjectiveThe study aimed to identify the determinants of thinness among school adolescents in the Legehida district of South Wollo Zone, Northeastern Ethiopia.MethodsA school-based, unmatched case-control study was conducted from January 20 to February 2, 2019. A total of 525 school-aged adolescents (175 cases and 350 controls) from the Legehida district were enrolled using a multistage sampling technique. Data were collected through interview-administered questionnaires and anthropometric measurements. EpiData version 3.1 was used for data entry, while Anthroplus software was employed for anthropometric measurement entry and analysis. The data were then exported to SPSS version 25 for further analysis. Bivariate and multivariable logistic regression analyses were performed to assess the determinants of adolescent thinness.ResultsIn this study, thinness among school adolescents was significantly associated with several factors: the absence of a latrine at home [AOR = 8.2, 95% CI (3.8, 8.17)], meal skipping per day [AOR = 3.1, 95% CI (1.2, 7.3)], inadequate consumption of fruits and vegetables [AOR = 7.5, 95% CI (3.9, 14.5)], having more than four household members [AOR = 13.6, 95% CI (7.1, 26)], and the consumption of unsafe water [AOR = 7.7, 95% CI (3.8, 15.6)].Conclusions and recommendationsThe absence of latrines and access to clean water, dietary factors, and family size emerged as significant contributors to adolescent thinness in this study. Addressing the nutritional challenges faced by adolescents will require collaborative efforts across sectors.

Screening the Potential f Fungal Derived Bioherbicide in Weed Management

Synthetic herbicides have long been a cornerstone of modern agriculture, providing effective weed control but often at significant environmental and health costs. These chemicals can persist in the environment, leach into groundwater, and harm non-target organisms, including humans. Additionally, the overuse of synthetic herbicides has led to the development of herbicide-resistant weeds, further complicating weed management strategies. In response to these challenges, researchers and farmers alike are increasingly turning to bioherbicides derived from fungi as a sustainable alternative. Fungal bioherbicides harness the natural antagonistic properties of fungi to target weeds. Unlike synthetic herbicides, which are chemically synthesized and often broad-spectrum in action, fungal bioherbicides utilize either the fungi themselves as pathogens or their metabolites to disrupt weed growth. This approach offers several distinct advantages:Target Specificity: Fungal bioherbicides can be highly specific to certain weed species or even to specific stages of weed growth. This specificity reduces collateral damage to non-target plants and organisms, making them particularly suitable for environmentally sensitive areas such as organic farms, riparian zones, and protected ecosystems. Environmental Friendliness: Unlike synthetic herbicides that can persist in the environment and accumulate in soil and water bodies, fungal bioherbicides generally have lower persistence. They degrade more rapidly and often have minimal impact on non-target organisms, thereby preserving biodiversity and ecosystem health. Reduced Risk of Resistance: Synthetic herbicides often face the challenge of herbicide-resistant weeds, which evolve due to continuous and widespread use. Fungal bioherbicides, by contrast, pose a lower risk of resistance development. This is because they typically act through multiple modes of action or biochemical pathways within the weed, making it harder for weeds to develop resistance mechanisms. Research into fungal-derived bioherbicides is actively exploring and harnessing these advantages. Scientists are screening diverse fungal species to identify potent pathogens or metabolites that effectively inhibit weed growth. Moreover, advances in biotechnology and genetic engineering allow for the enhancement of fungal strains to optimize their bioherbicidal properties while ensuring safety and efficacy. One promising example is the use of fungal pathogens like Phomamacrostoma and Colletotrichum truncatum, which have demonstrated efficacy against various weed species including common agricultural weeds like velvetleaf and pigweed. These fungi infect weeds through mechanisms such as spore attachment, penetration of plant tissues, and secretion of phytotoxic metabolites that inhibit weed growth. In addition to their direct impact on weed management, fungal bioherbicides contribute to sustainable agricultural practices by reducing reliance on synthetic chemicals. They align with principles of integrated pest management (IPM) by offering a biological control method that complements cultural and mechanical weed control strategies. Moving forward, continued research and development efforts are essential to refine fungal bioherbicides, optimize application techniques, and expand their practical use in diverse agricultural settings. Challenges such as formulation stability, cost-effectiveness, and regulatory approvals also need to be addressed to facilitate widespread adoption by farmers.

Facilitating outstanding engineering faculty members through training from recruitment to retirement

Most of the higher engineering education institutions don't focus on continuous training of their faculty members from recruitment to retirement (R to R). Because of this, the quality of performance of untrained faculty members gradually reduces and this impacts the attributes of their graduates, sporadic contribution to knowledge capital, and poor return on the investments (ROI) in engineering education. There is a need for an integrated and dynamic model for the training and development of engineering faculty members. The objectives of this research are to assess the literature on faculty development; to identify the total needs of the engineering faculty members from recruitment to retirement (R to R); to suggest effective and efficient methods of planned faculty development; and to validate the suggested process of development through a set of engineering institutions. The action research method has been adopted to assess the global literature, and consult multinational companies, local engineering companies, and alumni on their needs. It is found that ‘Faculty Development Courses’ are required for all engineering faculty members from entry to exit to facilitate meritocracy. A critical review of the literature revealed that most of the researchers have focused their research on entry-level faculty members or some middle-level faculty members. Only a few institutes focused on the senior members. Hence, this study focused on lifelong faculty development courses from entry-level to exit level. The training needs assessment was based on the feedback from 396 entry-level faculty members who were purposefully included in this research. The outcomes are presented in seven parts: (1) Entry-level faculty development programs (FDPs), (2) Getting recognized, (3) Middle-level FDPs, (4) Student personnel administration, (5) Senior-level FDPs, (6) Advanced-level FDPs, and (7) Radical innovations. This research provides a 360-degree assessment and creates a guide both for the educational administrators and faculty members to reach excellence. Learning is a lifelong process. The suggestions were validated through a set five of institutions. and they started implementing them. The continuous process of faculty development from recruitment to retirement has been appreciated but it may take several years to institutionalize it. Limitations of this study are a smaller number of faculty members (396) and suggestions for future research have also been indicated. This gave a promising cost-effective faculty development process at every stage of faculty growth and resulted in outstanding institutes with high-performing faculty members. Further, these faculty members contributed to human and knowledge capital.

Photoluminescence probing of light absorption centers at silica laser damage

We use photoluminescence (PL) imaging to study damage growth precursors within laser damage sites on the surface of silica. Damage site evolution is induced by multiple shots of UV nanosecond pulsed laser at various energy densities and monitored throughout the early stages of growth. Wide-field PL imaging rapidly locates microscopic light absorption centers within the silica damage site. Our quantitative analysis shows that damage sites with strong local PL intensity show a higher probability of growth upon subsequent laser pulses. Scanning electron microscopy (SEM) paired with a study of PL spectrum shows that the strong PL intensity appears from the subsurface fractures with high defect density, which provides a local light absorption center leading to significant damage growth. We believe that this result offers an efficient optical damage mitigation strategy by providing a rapid and non-destructive optical inspection approach.

Influence of Diverse Growing Environments and Plant Densities on Phenological Development and Agrometeorological Indices of Groundnut (Arachis hypogaea L.) in the Hyper Arid Zone of Rajasthan, India

Groundnut (Arachis hypogaea L.) stands as a significant oilseed crop globally. The growth, development, and productivity of these plants are notably affected by the adverse impacts of global climate change. Therefore, the current study sought to examine how diverse growing environments and planting densities influence the phenological development of groundnut in the hyper-arid zone of Rajasthan, India. A field experiment spanning the kharif seasons of 2017, 2018, and 2019 was conducted at Krishi Vigyan Kendra, Swami Keshwanand Rajasthan Agricultural University, Bikaner, India. The experiment laid out in split-plot design with four replications. The treatments included three main plots for growing environments (sowing on May 15, May 30, and June 15) and three sub-plots for planting densities (1.67 lakh ha-1, 2.50 lakh ha-1 and 3.33 lakh ha-1).. The outcomes of the field experiment indicates that sowing groundnut on May 30 was statistically on par with sowing on June 15 and resulted in higher values of GDD, helio thermal units (HTU), PTI, heat use efficiency (HUE), photothermal use efficiency (PUE), and heliothermal use efficiency, as well as hygrothermal use efficiency (Hg TUE-I and II) at the initiation of flowers and peg formation stages. However, at later growth stages significantly higher values of GDD, HTU, HUE, PUE, HgTUE-I and II were observed with the May 15 sowing. These values gradually decreased with delayed sowing up to May 30 and June 15. Further, increasing the planting density from 1.67 lakh ha-1, 2.50 lakh ha-1 and 3.33 lakh ha-1 significantly enhanced the HTU, HUE, PUE, HgTUE-I and II at various phenological stages of groundnut. Therefore, these findings underscore the significance of precise timing and density control in maximizing groundnut yields under challenging environmental circumstances. By understanding and modifying these variables, farmers can mitigate the adverse effects of climate change and enhance groundnut productivity, especially in extremely arid areas like Rajasthan.

Determining Critical Weed Competition at Different Weed Free Periods in Linseed in Holeta District Central Ethiopia

A substantial proportion of linseed yield is lost due to weeds in the Holeta area of Central Ethiopia. The weeds infest the crop fields during the early growth stage and consume growth resources. To protect the crops from weeds, farmers manage their fields using cultural practices. However, there is a knowledge gap between farmers on critical weed removal time for the management of the weeds from the crop. Therefore, it is assumed that determining the weed-free period after the sowing of linseed to control the weeds is necessary. The experiment was designed to determine the suitable weed-free period for the control of weeds and increasing linseed production. The trial was treated with different weed-free periods before 20, 30, 40, 50, and 60 days of sowing; and after 20, 30, 40, 40, and 60 days of sowing, twice hand weeding, weed-free, and control. The treatments were organized in a Randomized Complete Block Design (RCBD) replicated three times. It was found that Galinsogapulviflora was the most dominant weed, contributing to 18% of the total weeds present in the fields. Plots treated with weed-free after 20 days of sowing produced superior results in terms of reduction of weed dry weight by 100%, increased number of bolls per plant by 3.08 folds, stand count by 245%, and grain yield by 11 folds as compared to untreated check respectively. Hence, making weed free of linseed after 20 days of sowing is recommended for the management of various weeds in linseed.

Microbial influence on the larval survival of Japanese eel Anguilla japonica: Antibiotic-mediated alterations and biomarker isolation.

In rearing systems for the Japanese eel Anguilla japonica, although it is assumed that microorganisms influence larval survival and mortality, particularly during the early stages of growth, the effects of bacterial communities on larval survival have yet to be sufficiently determined. In this study, we compared the bacterial communities associated with larval survival at three stages of eel growth. To artificially alter bacterial communities and assess larval survival, eel larvae were treated with 11 types of antibiotic, and larval survival and bacterial characteristics were compared between the antibiotic-treated and antibiotic-free control groups. Throughout the three growth stages, eels treated with four antibiotics (polymyxin B, tetracycline, novobiocin, and erythromycin) had survival rates higher than those in the control groups. The bacterial communities of surviving larvae in the control and antibiotic groups and dead larvae in the control groups were subsequently analyzed using 16S rRNA gene amplicon sequencing. PERMANOVA analysis indicated that these three larval groups were characterized by significantly different bacterial communities. We identified 14 biomarker amplicon sequence variants (ASVs) of bacterial genera such as Oceanobacter, Alcanivorax, Marinobacter, Roseibium, and Sneathiella that were enriched in surviving larvae in the antibiotic treatment groups. In contrast, all four biomarker ASVs enriched in dead larvae of the control groups were from bacteria in the genus Vibrio. Moreover, 52 bacterial strains corresponding to nine biomarkers were isolated using a culture method. To the best of our knowledge, this is the first study to evaluate the bacterial communities associated with the survival and mortality of larvae in during the early stages of Japanese eel growth and to isolate biomarker bacterial strains. These findings will provide valuable insights for enhancing larval survival in the eel larval rearing systems from a microbiological perspective.

Effect of Growth Stage-based Water Stress on Yield and Water Use Efficiency of Tomatoes (Solanum lycopersicon L.) in Semi-arid Regions of Tigray, Ethiopia

Water availability is a major concern in regions with limited water resources. Implementation of best irrigation water management methods can maximize crop yields and irrigation water use efficiency. An experiment was conducted in Laelay Koraro district, Tigray, Ethiopia for two consecutive years (2018 and 2019 off seasons) to investigate the effect of growth stage-based deficit irrigation on tomato yield, yield characteristics and water usage efficiency. The experiment used a randomized complete block design (RCBD) with three replications. The treatments were three irrigation levels (100%, 50%, and 25% of crop irrigation requirement) and four FAO-defined tomato growth stages (initial, developmental, mid, and late seasons). Data on agronomic parameters and irrigation water were collected and analyzed statistically. The results revealed that reducing irrigation amount by up to 75% during the development growth stage significantly decreased marketable yield by up to 66.5%. However, the highest water use efficiency (9.2kgm-3) was achieved by reducing irrigation amount by 75% at the end-growth stage of tomato. Treatments with the lowest water use efficiency (3.5kgm-3) were those receiving 75% less irrigation amount than the full requirement during the development growth stage. Irrigation deficit up to 75% of the full requirement during tomato development stages greatly affect marketable yield and water use efficiency. Therefore, the tomato crop is highly susceptible to water stress when receiving more than a 50% reduction in full irrigation requirement during its developmental growth stage.

Predicting canopy chlorophyll concentration in citronella crop using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imagery

Unmanned Aerial Vehicle (UAV) remote sensing in precision agriculture (PA) is a promising technique for managing crop inputs. The high spatial-resolution data enables extensive examination of the crop canopy, including identifying low-chlorophyll patches for initiating prophylactic measures as early as possible. In this study DJI M-200 equipped with MicaSense Altum multispectral camera was used to acquire multispectral images of citronella fields under various nutrient treatments at different growth stages. The study assessed the relevance of Machine Learning (ML) on multispectral images to predict citronella chlorophyll concentrations. To predict the crop canopy chlorophyll concentration for citronella, we evaluated Random Forest (RF), Support Vector Machine (SVM) and Partial Least Square (PLS) machine learning models. Based on the Rsquare value of all three models, the SVM machine learning model could best predict the crop canopy chlorophyll concentration with coefficient of determination R2 (0.79), root mean square error (0.05) and mean absolute error (0.04) respectively. The correlation between predicted chlorophyll contents and selected Vegetation Indices (VIs) also demonstrated significant relationship, implying that these can serve as a valuable indicator of crop canopy chlorophyll, which in turn can be used for providing insights into crop health, vigor, and productivity. This study showed that by employing UAV multispectral images and machine learning models the spatial distributions of chlorophyll concentration in a citronella crop at different growth phases can be predicted accurately.

Effect of initial inoculum on the temporal and spatial dynamics of wheat blast under field conditions in Bolivia.

Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared to the Gompertz and exponential models. The non-linear logistic infection rates (rL) were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial cluster pattern according to autocorrelation analysis and Moran's Index (I) values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial cluster pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB, and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

Effect of initial inoculum on the temporal and spatial dynamics of wheat blast under field conditions in Bolivia.

Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared to the Gompertz and exponential models. The non-linear logistic infection rates (rL) were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial cluster pattern according to autocorrelation analysis and Moran's Index (I) values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial cluster pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB, and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

Algorithm for Corn Crop Row Recognition during Different Growth Stages Based on ST-YOLOv8s Network

Corn crop row recognition during different growth stages is a major difficulty faced by the current development of visual navigation technology for agricultural robots. In order to solve this problem, an algorithm for recognizing corn crop rows during different growth stages is presented based on the ST-YOLOv8s network. Firstly, a dataset of corn crop rows during different growth stages, including the seedling stage and mid-growth stage, is constructed in this paper; secondly, an improved YOLOv8s network, in which the backbone network is replaced by the swin transformer (ST), is proposed in this paper for detecting corn crop row segments; after that, an improved supergreen method is introduced in this paper, and the segmentation of crop rows and background within the detection frame is achieved utilizing the enhanced method; finally, the corn crop row lines are identified using the proposed local–global detection method, which detects the local crop rows first, and then detects the global crop rows. The corn crop row segment detection experiments show that the mean average precision (MAP) of the ST-YOLOv8s network during different growth stages increases by 7.34%, 11.92%, and 4.03% on average compared to the MAP of YOLOv5s, YOLOv7, and YOLOv8s networks, respectively, indicating that the ST-YOLOv8s network has a better crop row segment detection effect compared to the comparison networks. Corn crop row line detection experiments show that the accuracy of the local–global detection method proposed in this paper is improved by 17.38%, 10.47%, and 5.99%, respectively, compared with the accuracy of the comparison method; the average angle error is reduced by 3.78°, 1.61°, and 0.7°, respectively, compared with the average angle error of the comparison method; and the average fitting time is reduced by 5.30 ms, 18 ms, and 33.77 ms, respectively, compared with the average fitting time of the comparison method, indicating that the local–global detection method has a better crop row line detection effect compared to the comparison method. In summary, the corn crop row recognition algorithm proposed in this paper can well accomplish the task of corn crop row recognition during different growth stages and contribute to the development of crop row detection technology.

Evaluation of the monitoring capability of various vegetation indices and mainstream satellite band settings for grassland drought

In the context of global climate change and increasing human activities, grassland drought has become increasingly severe and complex. The monitoring of grassland drought is crucial for reducing drought-related losses and ensuring national ecological security. This study used the coupled PROSPECT and SAIL radiative transfer models (PROSAIL) to simulate canopy reflectance, considering factors such as grassland growth stages and varying drought conditions. Our objective was to reveal the spectral response characteristics of grasslands to varying drought conditions and identify sensitive spectral bands suitable for drought monitoring during different grassland growth stages. We aligned commonly available satellite bands from moderate resolution imaging spectroradiometer (MODIS), Sentinel 2, Landsat 8, WorldView 2, and Gaofen 2 (GF 2) with these sensitive bands to assess the capabilities of existing satellite data for drought monitoring. Furthermore, this research evaluated the suitability of 16 commonly used remote sensing vegetation indices for grassland drought monitoring, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Ratio Vegetation Index (RVI), Difference Vegetation Index (DVI), Modified Soil Adjusted Vegetation Index (MSAVI), Atmospherically Resistant Vegetation Index (ARVI), Modified Normalized Difference Water Index (MNDWI), Global Vegetation Moisture Index (GVMI), Land Surface Water Index (LSWI), Visible and Shortwave Infrared Drought Index (VSDI), Water index(WI), Moisture Stress Index(MSI), Normalized Difference Water Index(NDWI), Normalized Difference Infrared Index (NDII), Photochemical Reflectance Index (PRI), and Optimized Soil-Adjusted Vegetation Index (OSAVI). The simulation and analysis results revealed: 1) Grassland in different growth stages exhibit similar sensitivities to certain spectral bands, namely those within the ranges of 540 nm–720 nm, 1250 nm–1690 nm, 1805 nm–2190 nm, and 2264 nm–2500 nm, which are more sensitive to various drought conditions. 2) Suitable vegetation indices for both growing and stable stages include NDII, MSI, PRI, LSWI, and GVMI, with silhouette coefficients exceeding 0.6 for the growing stage and 0.7 for the stable stage. The least suitable vegetation index is DVI, with an average silhouette coefficient of 0.15 over the entire growth stage. 3) From the spectral band perspective, among the five assessed satellites, MODIS Band 7 exhibits the highest sensitivity to water content across all satellite bands. MODIS's band configuration is most suitable for monitoring grassland drought during different growth stages, while WorldView 2's band configuration is the least suitable.